1. Field of the Invention
The present invention relates to methods and object storage systems that allow re-filtering and re-classification of one or more objects via metadata without directly accessing the object associated with the metadata.
2. Background Art
Currently, there is much interest in storage systems that can be used to store a variety of objects. Such systems may, for example, be used to store digital data, analog data, objects de art, manufactured components, paper documents, other forms of storage media such as magnetic tape, optical disk, holographic storage, and the like. Therefore, in the context of data storage systems, Information Lifecycle Management (“ILM”) approaches, including data archive techniques, resource management techniques, and data warehousing, typically use a data classification mechanism with data entities such as data objects in object based storage, files in file systems, data sets in mainframe systems, or table or matrix subsets of a database.
In such storage systems, the common management approach is to use a classification system, i.e., when data objects are first received in the storage system, they are individually added to some classification grouping. When one of the other stored objects delineated above (e.g., a painting—object de art) are added to a storage system intended to manage such objects, it is also generally placed in the system according to some consistent classification system. Common archive and compliance data storage solutions invoke a data management approach classifying data objects individually into specific classifications.
The current art is based on a technique that uses a filter to process the data and other system metadata about the object in order to identify the preferred specific classification for a particular object. The filtering process must resolve classification ambiguity problems where there are many almost equivalent potential class assignments for any particular data object. However, a minor change in the focus of the business could drive a significant change in the filtering process (and thus results) which in turn could actually require every object in the system to be read again and reclassified for correct system operation. Today this would be an overwhelming performance problem. Current systems avoid this problem rather than solving it.
Accordingly, there exists a need in the prior art for improved methods and systems for filtering and reclassifying stored data.